Search results for: effect of collaborative learning

Authors: Yash Bingi, Yiqiao Yin

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Reduction of child mortality is an ongoing struggle and a commonly used factor in determining progress in the medical field. The under-5 mortality number is around 5 million around the world, with many of the deaths being preventable. In light of this issue, Cardiotocograms (CTGs) have emerged as a leading tool to determine fetal health. By using ultrasound pulses and reading the responses, CTGs help healthcare professionals assess the overall health of the fetus to determine the risk of child mortality. However, interpreting the results of the CTGs is time-consuming and inefficient, especially in underdeveloped areas where an expert obstetrician is hard to come by. Using a support vector machine (SVM) and oversampling, this paper proposed a model that classifies fetal health with an accuracy of 99.59%. To further explain the CTG measurements, an algorithm based on Randomized Input Sampling for Explanation ((RISE) of Black-box Models was created, called Feature Alteration for explanation of Black Box Models (FAB), and compared the findings to Shapley Additive Explanations (SHAP) and Local Interpretable Model Agnostic Explanations (LIME). This allows doctors and medical professionals to classify fetal health with high accuracy and determine which features were most influential in the process.

Keywords: machine learning, fetal health, gradient boosting, support vector machine, Shapley values, local interpretable model agnostic explanations

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Authors: Asmae Tafraouti, Yasmina Layouni

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The fabrication of cylindrical Tungsten micro-tools with a high aspect ratio is a real challenge because of several constraints that come into during their manufacture. In this paper, we will describe the process used to fabricate these micro-tools. It consists of using electrochemical etching. We will also present the optimal protocol that makes it possible to fabricate micro-tools with a high aspect ratio in a reproducible way. Next, we will show the limit of the experimental parameters chosen to manufacture micro-tools from a wire with an initial diameter of Φ_0=250µm. The protocol used allows obtaining an average diameter of Φ=88µm ±1 µm over a length of L=3.5mm.

Keywords: drop-off effect, electrochemical etching, micro-electrical discharge machining, tungsten micro-tools

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Authors: A. I. O. Zaid

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Deep drawing is considered to be the most widely used sheet metal forming processes among the particularly in automobile and aircraft industries. It is widely used for manufacturing a large number of the body and spare parts. In its simplest form it may be defined as a secondary forming process by which a sheet metal is formed into a cylinder or alike by subjecting the sheet to compressive force through a punch with a flat end of the same geometry as the required shape of the cylinder end while it is held by a blank holder which hinders its movement but does not stop it. The punch and die profile radii play In this paper, the effects of punch and die profile radii on the autographic record, the minimum thickness strain location where the cracks normally start and cause the fracture, the maximum deep drawing force and the total consumed work in the drawing flat ended cylindrical brass cups are investigated. Five punches and five dies each having different profile radii were manufactured for this investigation. Furthermore, their effect on the quality of the drawn cups is also presented and discussed. It was found that the die profile radius has more effect on the maximum drawing force and the total consumed work than the punch profile radius.

Keywords: punch and die profile radii, deep drawing process, maximum drawing force, total consumed work, quality of produced parts, flat ended cylindrical brass cups

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Authors: Shlomit Hon-Snir, Sharon Teitler-Regev, Anabel Lifszyc Friedlander

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Tourism, one of the world's largest and fastest growing industries, exerts a major economic influence. The number of international tourists is growing every year, and the relative portion of independent (FIT) tourists is growing as well. The characteristics of independent tourists differ from those of tourists who travel in organized trips. The purpose of the research is to identify the factors that affect the individual tourist's expenses in Israel: total expenses, expenses per day, expenses per tourist, expenses per day per tourist, accommodation expenses, dining expenses and transportation expenses. Most of the research analyzed the total expenses using OLS regression. The determinants influencing expenses were divided into four groups: budget constraints, socio-demographic data, psychological characteristics and travel-related characteristics. Since the effect of each variable may change over different levels of total expenses the quantile regression (QR) theory will be applied. The current research will use data collected by the Israeli Ministry of Tourism in 2015 from individual independent tourists at the end of their visit to Israel. Preliminary results show that: At lower levels of expense, only income has a (positive) effect on total expenses, while at higher levels of expense, both income and length of stay have (positive) effects. -The effect of income on total expenses is higher for higher levels of expenses than for lower level of expenses. -The number of sites visited during the trip has a (negative) effect on tourist accommodation expenses only for tourists with a high level of total expenses. Due to the increasing share of independent tourism in Israel and around the world and due to the importance of tourism to Israel, it is very important to understand the factors that influence the expenses and behavior of independent tourists. Understanding the factors that affect independent tourists' expenses in Israel can help Israeli policymakers in their promotional efforts to attract tourism to Israel.

Keywords: independent tourist, quantile regression theory, tourism expenses, tourism

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Authors: Bassim Shaheen Bachy, Jörg Franke

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In this study, a three dimensional numerical heat transfer model has been used to simulate the laser structuring of polymer substrate material in the Three-Dimensional Molded Interconnect Device (3D MID) which is used in the advanced multi-functional applications. A finite element method (FEM) transient thermal analysis is performed using APDL (ANSYS Parametric Design Language) provided by ANSYS. In this model, the effect of surface heat source was modeled with Gaussian distribution, also the effect of the mixed boundary conditions which consist of convection and radiation heat transfers have been considered in this analysis. The model provides a full description of the temperature distribution, as well as calculates the depth and the width of the groove upon material removal at different set of laser parameters such as laser power and laser speed. This study also includes the experimental procedure to study the effect of laser parameters on the depth and width of the removal groove metal as verification to the modeled results. Good agreement between the experimental and the model results is achieved for a wide range of laser powers. It is found that the quality of the laser structure process is affected by the laser scan speed and laser power. For a high laser structured quality, it is suggested to use laser with high speed and moderate to high laser power.

Keywords: laser structuring, simulation, finite element analysis, thermal modeling

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Authors: Hye Kyung Kim, Myung-Gyou Kim, Kang-Hyun Leem

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It has been reported that deer antler extract has bone-strengthening activity and effectively used in bone diseases therapy. However, little is known about the cellular and molecular mechanism of this effect. The upper section, mid section, and base of the antler has been known to exhibit different biological properties. Present study investigated the effects of these three parts of deer antler extracts on bone formation and resorption. The effects of deer antler extracts (DH) on bone formation were determined by cell proliferation, alkaline phosphatase (ALP) activity, collagen synthesis, and mineralization in human osteoblastic MG-63 cells. The effect on bone resorption was determined by osteoclastogenesis from bone marrow-derived precursor cells driven by RANKL. Ethanol extracts of DH (50 ~ 100 µg/ml) dose-dependently increased cell proliferation, and upper part increased the cell proliferation by 118.4% while mid and base parts increased proliferation by 107.8% and 102.3%, respectively. ALP activity was significantly increased by upper part of the DH treatment. After enhancement of ALP activity, significant augmentation of collagen synthesis and calcification assessed by Sirus red and Alzarin red staining, respectively, was observed in upper part of the DH treatment. The effect of DH on bone resorption was not observed in all three parts of the DH. These results could provide a mechanistic explanation for the bone-strengthening effects of DH.

Keywords: alkaline phosphatase, collagen synthesis, deer antler, osteoblastic MG-63 cells

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Authors: Mingxin Li, Liya Ni

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Autonomous parking is a valuable feature applicable to many robotics applications such as tour guide robots, UV sanitizing robots, food delivery robots, and warehouse robots. With auto-parking, the robot will be able to park at the charging zone and charge itself without human intervention. As compared to self-driving vehicles, auto-parking is more challenging for a small-scale mobile robot only equipped with a front camera due to the camera view limited by the robot’s height and the narrow Field of View (FOV) of the inexpensive camera. In this research, auto-parking of a small-scale mobile robot with a front camera only was achieved in a four-step process: Firstly, transfer learning was performed on the AlexNet, a popular pre-trained convolutional neural network (CNN). It was trained with 150 pictures of empty parking slots and 150 pictures of occupied parking slots from the view angle of a small-scale robot. The dataset of images was divided into a group of 70% images for training and the remaining 30% images for validation. An average success rate of 95% was achieved. Secondly, the image of detected empty parking space was processed with edge detection followed by the computation of parametric representations of the boundary lines using the Hough Transform algorithm. Thirdly, the positions of the entrance point and center of available parking space were predicted based on the robot kinematic model as the robot was driving closer to the parking space because the boundary lines disappeared partially or completely from its camera view due to the height and FOV limitations. The robot used its wheel speeds to compute the positions of the parking space with respect to its changing local frame as it moved along, based on its kinematic model. Lastly, the predicted entrance point of the parking space was used as the reference for the motion control of the robot until it was replaced by the actual center when it became visible again by the robot. The linear and angular velocities of the robot chassis center were computed based on the error between the current chassis center and the reference point. Then the left and right wheel speeds were obtained using inverse kinematics and sent to the motor driver. The above-mentioned four subtasks were all successfully accomplished, with the transformed learning, image processing, and target prediction performed in MATLAB, while the motion control and image capture conducted on a self-built small scale differential drive mobile robot. The small-scale robot employs a Raspberry Pi board, a Pi camera, an L298N dual H-bridge motor driver, a USB power module, a power bank, four wheels, and a chassis. Future research includes three areas: the integration of all four subsystems into one hardware/software platform with the upgrade to an Nvidia Jetson Nano board that provides superior performance for deep learning and image processing; more testing and validation on the identification of available parking space and its boundary lines; improvement of performance after the hardware/software integration is completed.

Keywords: autonomous parking, convolutional neural network, image processing, kinematics-based prediction, transfer learning

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Authors: Akano Benedict Ubawuike

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This study investigated the effects of pre-laboratory discussion on physics students’ acquisition of science process skills. The study design was quasi-experimental and purposive sampling technique was applied in selecting two schools in Kontagora Town for the research based on the availability of a good physics laboratory. Intact classes already grouped by the school for the sake of small laboratory space and equipment, comprising Thirty (30) students, 15 for experimental group in School A and 15 for control in school B were the subjects for the research. The instrument used for data collection was the lesson prepared for pre – practical discussion and researcher made Science Process Skill Test (SPST ) and two (2) research questions, and two (2) research hypotheses were developed to guide the study. The data collected were analyzed using means and t-Test statistics at 0.05 level of significance. The study revealed that pre-laboratory discussion was found to be more efficacious in enhancing students’ acquisition of science process skills. It also revealed that gender, had no significant effect on students’ acquisition of science process skills. Based on the findings, it was recommended among others that teachers should encourage students to develop interest in practical activities by engaging them in pre-laboratory discussion and providing instructional materials that will challenge them to be actively involved during practical lessons. It is also recommended that Ministries of Education and professional organizations like Science Teachers' Association of Nigeria (STAN) should organize workshops, seminars and conferences for physics teachers and Physics concepts should be taught with practical activity so that the students will do science instead of learning about science.

Keywords: physics, laboratory, discussion, students, acquisition, science process skills

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Authors: S. Salah, S. A. El-Masry, H. F. Sheba, R. A. El-Banna, W. Saad

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Background: Familial Mediterranean fever (FMF) has episodic or subclinical inflammation that may lead to a decrease in bone mineral density (BMD). Objective: To assess BMD in Egyptian children with FMF on genetic basis. Subjects and Methods: A cross sectional study included 45 FMF patients and 25 control children of both sexes, with age range between 3-16 years old. The patients were reclassified into 2 groups: Group I (A) 23 cases used colchicines for 1 month or less, and Group I (B) 22 cases used colchicines for more than 6 months. For both patients and control, MEFV mutations were defined using molecular genetics technique and BMD was measured by DXA at 2 sites: proximal femur and the lumber spines. Results: four frequent gene mutations were found in the patient group: E148Q (35.6%), V726A (33.3%), M680I (28.9.0%) and M694V (2.2%). There were also 4 heterozygous gene mutations in 40% of control children. Patients received colchicines treatment for less than 1 month had highly significant lower values of BMD at femur and lumber spines than control children (p<0.05). Patients received colchicines treatment for more than 6 months had improved values of BMD at femur compared to control, but there were still significant differences between them at lumbar spine (p>0.05). There are insignificant effect of type of gene mutation on BMD and the risk of osteopenia among the patients. Conclusion: FMF had significant effect on BMD. However, regular use of colchicines treatment improves this effect mainly at femur.

Keywords: familial mediterranean fever, bone mineral density, genes, children

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Authors: Ahmed M. Eltohamy

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In this paper, an experimental and numerical study was adopted to investigate the effect geogrid soil reinforcement pre-stressing on the pressure settlement relation of sand bed supporting a strip foundation. The studied parameters include foundation depth and pre-stress ratio for the cases of one and two pre-stressed reinforcement layers. The study reflected that pre-stressing of soil reinforcement resulted in a marked enhancement in reinforced bed soil stiffness compared to the reinforced soil without pre-stress. The best benefit of pre-stressing reinforcement was obtained as the overburden pressure and pre-straining ratio increase. Pre-stressing of double reinforcement topmost layers results in further enhancement of stress strain relation of bed soil.

Keywords: geogrid reinforcement, prestress, strip footing, bearing capacity

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Authors: Boudjema Nouara, Mameri Nabil

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Bacteria have played an important role in water contamination as a consequence of organic pollution. In this study, an electrocoagulation process was adopted to remove fecal contamination and pathogenic bacteria from waste water. The effect of anode/cathodes materials as well as operating conditions for bacteria removal from water, such as current intensity and initial pH and temperature. The results indicated that the complete removal was achevied when using aluminium anode as anode at current intensity of 3A, initial pH of 7-8 and electrolysis time of 30 minutes. This process showed a bactericidal effect of 95 to 99% for the total and fecal coliforms and 99% to 100% for Eschercichia coli and fecal Streptococci. A decrease of 72% was recorded for sulphite-reducing Clostridia. Thus, this process has the potential to be one the options for treatment where high amount of bacteria in wastewater river.

Keywords: bacteria, el Harrach river, electrocoagulation, wastewater, treatment

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Authors: Asmaa Selim, Peter Mizsey

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Bio-ethanol is considered of higher potential as a green renewable energy source owing to its environmental benefits and its high efficiency. In the present study, silver nanoparticles were in-situ generated in a poly (vinyl alcohol) in order to improve its potentials for pervaporation of ethanol-water mixture using solution-casting. Effect of silver content on the pervaporation separation index and the enrichment factor of the membrane at 15 percentage mass water at 40ᵒC was reported. Pervaporation data for nanocomposite membranes showed around 100% increase in the water permeance values while the intrinsic selectivity decreased. The water permeances of origin crosslinked PVA membrane, and the 2.5% silver loaded PVA membrane are 26.65 and 70.45 (g/m².kPa.h) respectively. The values of total flux and water flux are closed to each other, indicating that membranes could be effectively used to break the azeotropic point of ethanol-water. Effect of temperature on the pervaporation performance, permeation parameter and diffusion coefficient of both water and ethanol was discussed. The negative heat of sorption ∆Hs values calculated on the basis of the estimated Arrhenius activation energy values indicating that the sorption process was controlled by Langmuir’s mode. The overall results showed that the membrane containing 0.5 mass percentage of Ag salt exhibited excellent PV performance.

Keywords: bio-ethanol, diffusion coefficient, nanocomposite, pervaporation, poly (vinyl alcohol), silver nanoparticles

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Authors: A. Moussouni, L. Mouzai, M. Bouhadef

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Soil erosion is a very complex phenomenon, resulting from detachment and transport of soil particles by erosion agents. The kinetic energy of raindrop is the energy available for detachment and transport by splashing rain. The soil erodibility is defined as the ability of soil to resist to erosion. For this purpose, an experimental study was conducted in the laboratory using rainfall simulator to study the effect of the kinetic energy of rain (Ec) on the soil erodibility (K). The soil used was a sandy agricultural soil of 62.08% coarse sand, 19.14% fine sand, 6.39% fine silt, 5.18% coarse silt and 7.21% clay. The obtained results show that the kinetic energy of raindrops evolves as a power law with soil erodibility.

Keywords: erosion, runoff, raindrop kinetic energy, soil erodibility, rainfall intensity, raindrop fall velocity

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Authors: Anamika Devi

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Based on Vygotsky’s cultural, historical theory and Hedegaard’s concept of transition, this study aims to investigate to propose strategies to maintain digital wellbeing of children and parents during and post COVID pandemic. Due COVID 19 pandemic, children and families have been facing new challenges and sudden changes in their everyday life. While children are juggling to adjust themselves in new circumstance of onsite and online learning settings, parents are juggling with their work-life balance. A number of papers have identified that the COVID-19 pandemic has affected the lives of many families around the world in many ways, for example, the stress level of many parents increased, families faced financial difficulties, uncertainty impacted on long term effects on their emotional and social wellbeing. After searching and doing an intensive literature review from 2020 and 2021, this study has found some scholarly articles provided solution or strategies of reducing stress levels of parents and children in this unprecedented time. However, most of them are not underpinned by proper theoretical lens to ensure they validity and success. Therefore, this study has proposed strategies that are underpinned by theoretical lens to ensure their impact on children’s and parents' emotional wellbeing during and post COVID-19 era. The strategies will highlight on activities for positive coping strategies to the best use of family values and digital technologies.

Keywords: onsite and online learning, strategies, emotional wellbeing, tips, and strategies, COVID19

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Authors: Zachary Huffman, Joana Rocha

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Wall-pressure fluctuations induced by the turbulent boundary layer (TBL) developed over aircraft are a significant source of aircraft cabin noise. Since the power spectral density (PSD) of these pressure fluctuations is directly correlated with the amount of sound radiated into the cabin, the development of accurate empirical models that predict the PSD has been an important ongoing research topic. The sound emitted can be represented from the pressure fluctuations term in the Reynoldsaveraged Navier-Stokes equations (RANS). Therefore, early TBL empirical models (including those from Lowson, Robertson, Chase, and Howe) were primarily derived by simplifying and solving the RANS for pressure fluctuation and adding appropriate scales. Most subsequent models (including Goody, Efimtsov, Laganelli, Smol’yakov, and Rackl and Weston models) were derived by making modifications to these early models or by physical principles. Overall, these models have had varying levels of accuracy, but, in general, they are most accurate under the specific Reynolds and Mach numbers they were developed for, while being less accurate under other flow conditions. Despite this, recent research into the possibility of using alternative methods for deriving the models has been rather limited. More recent studies have demonstrated that an artificial neural network model was more accurate than traditional models and could be applied more generally, but the accuracy of other machine learning techniques has not been explored. In the current study, an original model is derived using a stepwise regression algorithm in the statistical programming language R, and TBL wall-pressure fluctuations PSD data gathered at the Carleton University wind tunnel. The theoretical advantage of a stepwise regression approach is that it will automatically filter out redundant or uncorrelated input variables (through the process of feature selection), and it is computationally faster than machine learning. The main disadvantage is the potential risk of overfitting. The accuracy of the developed model is assessed by comparing it to independently sourced datasets.

Keywords: aircraft noise, machine learning, power spectral density models, regression models, turbulent boundary layer wall-pressure fluctuations

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Authors: Shweta Hoyani, Charlie Oommen

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HAN-based liquid propellants are perceived as potential substitute for hydrazine in space propulsion. Storage stability for long service life in orbit is one of the key concerns for HAN-based monopropellants because of its reactivity with metallic and non-metallic impurities which could entrain from the surface of fuel tanks and the tubes. The end result of this reactivity directly affects the handling, performance and storability of the liquid propellant. Gaseous products resulting from the decomposition of the propellant can lead to deleterious pressure build up in storage vessels. The partial loss of an energetic component can change the ignition and the combustion behavior and alter the performance of the thruster. The effect of largely plausible metals- iron, copper, chromium, nickel, manganese, molybdenum, zinc, titanium and cadmium on the thermal decomposition mechanism of HAN has been investigated in this context. Studies involving different concentrations of metal ions and HAN at different preheat temperatures have been carried out. Effect of metal ions on the decomposition behavior of HAN has been studied earlier in the context of use of HAN as gun propellant. However the current investigation pertains to the decomposition mechanism of HAN in the context of use of HAN as monopropellant for space propulsion. Decomposition onset temperature, rate of weight loss, heat of reaction were studied using DTA- TGA and total pressure rise and rate of pressure rise during decomposition were evaluated using an in-house built constant volume batch reactor. Besides, reaction mechanism and product profile were studied using TGA-FTIR setup. Iron and copper displayed the maximum reaction. Initial results indicate that iron and copper shows sensitizing effect at concentrations as low as 50 ppm with 60% HAN solution at 80°C. On the other hand 50 ppm zinc does not display any effect on the thermal decomposition of even 90% HAN solution at 80°C.

Keywords: hydroxylammonium nitrate, monopropellant, reaction mechanism, thermal stability

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Authors: Ana Pego

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Environmental technologies were developed for decades. Clean technologies emerged a few years ago. In these perspectives, the use of cleantech technologies has become very important due the fact of new era of environmental feats. As such, the market itself has become more competitive, more collaborative towards a better use of clean technologies. This paper shows the importance of clean technologies in offshore energy sector in Portuguese market, its localization and its impact on economy. Clean technologies are directly related with renewable cluster and concomitant with economic and social resource optimization criteria, geographic aspects, climate change and soil features. Cleantech is related with regional development, socio-technical transitions in organisations. There are an economical and social combinations which allow specialisation of regions in activities, higher employment, reduce of energy costs, local knowledge spillover and, business collaboration and competitiveness. The methodology used will be quantitative (IO matrix for Portugal 2013) and qualitative (questionnaires to stakeholders). The mix of both methodologies will confirm whether the use of technologies will allow a positive impact on economic and social variables used on this model. It is expected a positive impact on Portuguese economy both in investment and employment taking in account the localization of offshore renewable activities. This means that the importance of offshore renewable investment in Portugal has a few points which should be pointed out: the increase of specialised employment, localization of specific activities in territory, and increase of value added in certain regions. The conclusion will allow researchers and organisation to compare the Portuguese model to other European regions in order to a better use of natural and human resources.

Keywords: cleantech, economic impact, localisation, territory dynamics

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Authors: Richard White, Anne Drabble, Maureen O’Neill

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The University of the Sunshine Coast (USC) offers secondary school students in the final two years of school (Years 11 and 12, 16 – 18 years of age) an opportunity to participate in a program which provides an accelerated pathway to tertiary studies. Whilst still at secondary school, the students undertake two first year university subjects that are required subjects in USC undergraduate degree programs. The program is called Integrated Learning Pathway (ILP) and offers a range of disciplines, including business, design, drama, education, and engineering. Between 2010 and 2014, 38% of secondary students who participated in an ILP program commenced undergraduate studies at USC following completion of secondary school studies. The research reported here considers “before and after” literacy and numeracy competencies of students to determine what impact participation in the ILP program has had on their academic skills. Qualitative and quantitative data has been gathered via numeracy and literacy testing of the students, and a survey asking the students to self-evaluate their numeracy and literacy skills, and reflect on their views of these academic skills. The research will enable improved targeting of teaching strategies so that students will acquire not only course-specific learning outcomes but also collateral academic skills. This enhancement of academic skills will improve undergraduate experience and improve student retention.

Keywords: academic skills enhancement, accelerated pathways, improved teaching, student retention

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Authors: Mohammad Javad Shakori, Esmaeil Babakhanzadeh Sajirani, Vajihe Esmaili

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Today, the increasing contamination is an environmental concern. There is relationship between plants and microorganisms many years ago. In this regard, an experiment was conducted in order to investigate the effect of different levels of lead across three levels ‘zero, 50, and 100 mg/L’ and Trichoderma Harzanium fungus across three levels ‘5, 10, and 15%’ in a factorial design in the form of fully randomized blocks in three replications under form conditions in the climatic conditions of Shahroud in Dehlama Village. This research was performed in 2014-2015 on cauliflower. In this experiment, chlorophyll a, b, total, cartenoid, phenol, flavonoid, and antioxidant properties of cauliflowers were measured. The results indicated that the greatest level of chlorophyll a (75.723 mg/wet weight), chlorophyll b (27.378 mg/wet weight), and total chlorophyll (109.074 mg/wet weight) was related to the interactive effects of 5% treatment of Trichoderma fungus and 0mg/L lead. The results also indicated that the greatest amount of antioxidant (79.88% of free radical) and flavonoides (22.889 mg of coercetin/g of dry weight) was related to the interactive effects of lead 50 mg/L and the treatment of Trichoderma fungus 5%. Further, the greatest level of phenol (21.33 mg of Gaelic acid/ dry weight) was related to the interactive effects of lead 100 mg/L and Trichoderma fungus 5% . As carotenoids are a type of antioxidant and precursor of vitamin A, with the development of alignment effect with other antioxidants such as the total phenol, flavonoid, achieved desirable levels of antioxidant.

Keywords: antioxidant, lead, flavonoid, cauliflower, chlorophyll

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Authors: Shilpagauri Prasad Ganpule

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The teaching of drama is considered as the most significant and noteworthy area in an ESL classroom. Diverse innovative techniques can be used to make the teaching of drama worthwhile and interesting. The paper presents the different innovative techniques that can be used while teaching Henrik Ibsen’s A Doll’s House [2007]. The innovative techniques facilitate students’ understanding and comprehension of the text. The use of the innovative techniques makes them explore the dramatic text and uncover a multihued arena of meanings hidden in it. They arouse the students’ interest and assist them overcome the difficulties created by the second language. The diverse innovative techniques appeal to the imagination of the students and increase their participation in the classroom. They help the students in the appreciation of the dramatic text and make the teaching learning situation a fruitful experience for both the teacher and students. The students successfully overcome the problem of L2 comprehension and grasp the theme, story line and plot-structure of the play effectively. The innovative techniques encourage a strong sense of participation on the part of the students and persuade them to learn through active participation. In brief, the innovative techniques promote the students to perform various tasks and expedite their learning process. Thus the present paper makes an attempt to present varied innovative techniques that can be used while teaching drama. It strives to demonstrate how the use of innovative techniques improve and enhance the students’ understanding and appreciation of Ibsen’s A Doll’s House [2007].

Keywords: ESL classroom, innovative techniques, students’ participation, teaching of drama

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Authors: Thi Huong Vu, Vijay Jayasena, Zhongxiang Fang, Gary Dykes

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D-pinitol (3-O-methyl ether of D-chiro-inosito) has been known to have health benefits for diabetic patients. Carob kibble has received attention due to the presence of high value D-pinitol and polyphenol antioxidants. D-pinitol was concentrated from carob kibble using submerged fermentation with Saccharomyces cerevisiae. Total carbohydrates and D-pinitol were determined by the phenol-sulphuric acid method and HPLC, respectively. The content of D-pinitol increased from approximately 43 to 70 mg/g dry weight after fermentation. The yeast consumed over 70% of total carbohydrates in carob kibble without any negative effect on D-pinitol content. A range of substrate medium pH’s from 5.0 – 7.0 had no significant effect on the removal of carbohydrates and D-pinitol. This method may provide a practical solution for production of D-pinitol from carob in a cost effective manner.

Keywords: carob kibble, d-pinitol, saccharomyces cerevisiae, submerged fermentation, total carbohydrates

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Authors: Jana Abu Ahmada, Zaineb Mohamed, Ilyasse Aksikas

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The linear quadratic control system of hyperbolic first order partial differential equations (PDEs) are presented. The aim of this research is to control chemical reactions. This is achieved by converting the PDEs system to ordinary differential equations (ODEs) using the method of characteristics to reduce the system to control it by using the integral reinforcement learning. The designed controller is applied to a catalytic cracking reactor. Background—Transport-Reaction systems cover a large chemical and bio-chemical processes. They are best described by nonlinear PDEs derived from mass and energy balances. As a main application to be considered in this work is the catalytic cracking reactor. Indeed, the cracking reactor is widely used to convert high-boiling, high-molecular weight hydrocarbon fractions of petroleum crude oils into more valuable gasoline, olefinic gases, and others. On the other hand, control of PDEs systems is an important and rich area of research. One of the main control techniques is feedback control. This type of control utilizes information coming from the system to correct its trajectories and drive it to a desired state. Moreover, feedback control rejects disturbances and reduces the variation effects on the plant parameters. Linear-quadratic control is a feedback control since the developed optimal input is expressed as feedback on the system state to exponentially stabilize and drive a linear plant to the steady-state while minimizing a cost criterion. The integral reinforcement learning policy iteration technique is a strong method that solves the linear quadratic regulator problem for continuous-time systems online in real time, using only partial information about the system dynamics (i.e. the drift dynamics A of the system need not be known), and without requiring measurements of the state derivative. This is, in effect, a direct (i.e. no system identification procedure is employed) adaptive control scheme for partially unknown linear systems that converges to the optimal control solution. Contribution—The goal of this research is to Develop a characteristics-based optimal controller for a class of hyperbolic PDEs and apply the developed controller to a catalytic cracking reactor model. In the first part, developing an algorithm to control a class of hyperbolic PDEs system will be investigated. The method of characteristics will be employed to convert the PDEs system into a system of ODEs. Then, the control problem will be solved along the characteristic curves. The reinforcement technique is implemented to find the state-feedback matrix. In the other half, applying the developed algorithm to the important application of a catalytic cracking reactor. The main objective is to use the inlet fraction of gas oil as a manipulated variable to drive the process state towards desired trajectories. The outcome of this challenging research would yield the potential to provide a significant technological innovation for the gas industries since the catalytic cracking reactor is one of the most important conversion processes in petroleum refineries.

Keywords: PDEs, reinforcement iteration, method of characteristics, riccati equation, cracking reactor

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Authors: Amr Emam, Joseph Victor, Mohamed Abd Elghany

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The paper presents the effect of the orbit inclination on the pointing error of the satellite antenna and consequently on its footprint on earth for a typical Ku- band payload system. The performance assessment is examined both theoretically and by means of practical measurements, taking also into account all additional sources of pointing errors, such as East-West station keeping, orbit eccentricity and actual attitude control performance. An implementation and computation of the sinusoidal biases in satellite roll and pitch used to compensate the pointing error of the satellite antenna coverage is studied and evaluated before and after the pointing corrections performed. A method for evaluation of the performance of the implemented biases has been introduced through measuring satellite received level from a tracking 11m and fixed 4.8m transmitting antenna before and after the implementation of the pointing corrections.

Keywords: satellite, inclined orbit, pointing errors, coverage optimization

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Authors: Jisong Zhang, Yinghua Zhao

Abstract:

The present study investigated the mechanical properties and microstructure of Ultra-High Performance Concrete (UHPC) containing supplementary cementitious materials (SCMs), such as fly ash (FA) and silica fume (SF), and to verify the synergistic effect in the ternary system. On the basis of 30% fly ash replacement, the incorporation of either 10% SF or 20% SF show a better performance compared to the reference sample. The efficiency factor (k-value) was calculated as a synergistic effect to predict the compressive strength of UHPC with these SCMs. The SEM of micrographs and pore volume from BJH method indicate a high correlation with compressive strength. Further, an artificial neural networks model was constructed for prediction of the compressive strength of UHPC containing these SCMs.

Keywords: artificial neural network, fly ash, mechanical properties, ultra-high performance concrete

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Authors: Claire Xu, Welton Wang, Manasvi Pinnaka, Anqi Pan, Michael Han

Abstract:

Hospitalizations account for one-third of the total health care spending in the US. Early risk detection and intervention can reduce this high cost and increase the satisfaction of both patients and physicians. Due to the lack of awareness of the potential arising risks in home environment, the opportunities for patients to seek early actions of clinical visits are dramatically reduced. This research aims to offer a highly personalized remote patients monitoring and risk assessment AI framework to identify the potentially preventable hospitalization for both acute as well as chronic diseases. A hybrid-AI framework is trained with data from clinical setting, patients surveys, as well as online databases. 20+ risk factors are analyzed ranging from activities, biometric info, demographic info, socio-economic info, hospitalization history, medication info, lifestyle info, etc. The AI model yields high performance of 87% accuracy and 88 sensitivity with 20+ features. This hybrid-AI framework is proven to be effective in identifying the potentially preventable hospitalization. Further, the high indicative features are identified by the models which guide us to a healthy lifestyle and early intervention suggestions.

Keywords: hospitalization prevention, machine learning, remote patient monitoring, risk prediction

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Authors: Nattapong Techarattanased

Abstract:

The purposes of this research are to make comparisons in respect of the behaviors on the use of the services of metered taxi classified by the demographic factor and to study the influence of the recognition on service quality having the effect on usage behaviors of metered taxi services of consumers in Bangkok Metropolitan Areas. The samples used in this research are 400 metered taxi service users in Bangkok Metropolitan Areas and use a questionnaire as the tool for collecting the data. Analysis statistics is mean and multiple regression analysis. Results of the research revealed that the consumers recognize the overall quality of services in each aspect include tangible aspects of the service, responses to customers, assurance on the confidence, understanding and knowing of customers which is rated at the moderate level except the aspect of the assurance on the confidence and trustworthiness which are rated at a high level. For the result of a hypothetical test, it is found that the quality in providing the services on the aspect of the assurance given to the customers has the effect on the usage behaviors of metered taxi services and the aspect of the frequency on the use of the services per month which in this connection. Such variable can forecast at one point nine percent (1.9%). In addition, quality in providing the services and the aspect of the responses to customers have the effect on the behaviors on the use of metered taxi services on the aspect of the expenses on the use of services per month which in this connection, such variable can forecast at two point one percent (2.1%).

Keywords: consumer behavior, metered taxi service, satisfaction, service quality

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Authors: N. Zhang, J. S. Kuang, S. Mogili

Abstract:

To investigate seismic performance of beam-column knee joints, four full-scale reinforced concrete beam-column knee joints, which were fabricated to simulate those in as-built RC frame buildings designed to ACI 318-14 and ACI-ASCE 352R-02, were tested under reversed cyclic loading. In the experimental programme, particular emphasis was given to the effect of horizontal reinforcement (in format of inverted U-shape bars) on the shear strength and ductility capacity of knee joints. Test results are compared with those predicted by four seismic design codes, including ACI 318-14, EC8, NZS3101 and GB50010. It is seen that the current design codes of practice cannot accurately predict the shear strength of seismically designed knee joints.

Keywords: large-scale tests, RC beam-column knee joints, seismic performance, shear strength

Procedia PDF Downloads 236

Authors: Seongcheol Kwon, Jeongmin Kim, Kwang Ryel Ryu

Abstract:

We assume an IoT-based smart-home environment where the on-off status of each of the electrical appliances including the room lights can be recognized in a real time by monitoring and analyzing the smart meter data. At any moment in such an environment, we can recognize what the household or the user is doing by referring to the status data of the appliances. In this paper, we focus on a smart-home service that is to activate a robot vacuum cleaner at right time by recognizing the user situation, which requires a situation-aware model that can distinguish the situations that allow vacuum cleaning (Yes) from those that do not (No). We learn as our candidate models a few classifiers such as naïve Bayes, decision tree, and logistic regression that can map the appliance-status data into Yes and No situations. Our training and test data are obtained from simulations of user behaviors, in which a sequence of user situations such as cooking, eating, dish washing, and so on is generated with the status of the relevant appliances changed in accordance with the situation changes. During the simulation, both the situation transition and the resulting appliance status are determined stochastically. To compare the performances of the aforementioned classifiers we obtain their learning curves for different types of users through simulations. The result of our empirical study reveals that naïve Bayes achieves a slightly better classification accuracy than the other compared classifiers.

Keywords: situation-awareness, smart home, IoT, machine learning, classifier

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Authors: Muhammad Umair, Tanveer Hussain, Khubab Shaker, Yasir Nawab, Muhammad Maqsood, Madeha Jabbar

Abstract:

The term comfort is defined as 'the absence of unpleasantness or discomfort' or 'a neutral state compared to the more active state'. Comfort mainly is of three types: sensorial (tactile) comfort, psychological comfort and thermo-physiological comfort. Thermophysiological comfort is determined by the air permeability and moisture management properties of the garment. The aim of this study was to investigate the effect of weave structure and picking sequence on the comfort properties of woven fabrics. Six woven fabrics with two different weave structures i.e. 1/1 plain and 3/1 twill and three different picking sequences: (SPI, DPI, 3PI) were taken as input variables whereas air permeability, wetting time, wicking behavior and overall moisture management capability (OMMC) of fabrics were taken as response variables and a comparison is made of the effect of weave structure and picking sequence on the response variables. It was found that fabrics woven in twill weave design and with simultaneous triple pick insertion (3PI) give significantly better air permeability, shorter wetting time and better water spreading rate, as compared to plain woven fabrics and those with double pick insertion (DPI) or single pick insertion (SPI). It could be concluded that the thermophysiological comfort of woven fabrics may be significantly improved simply by selecting a suitable weave design and picking sequence.

Keywords: air permeability, picking sequence, thermophysiological comfort, weave design

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Authors: Hireni Mankodi

Abstract:

The textile preforms for thermoplastic composite play a key role in providing the mechanical properties and gives the idea about preparing combination of yarn from Glass, Basalt, Carbon as reinforcement and PP, PET, Nylon as thermoplastic matrix at yarn stage for preforms to improve the quality and performance of laminates. The main objectives of this work are to develop the hybrid yarn using different yarn manufacturing process and prepare different performs using hybrid yarns. It has been observed that the glass/pp combination give homogeneous distribution in yarn. The proportion varied to optimize the glass/pp composition. The different preform has been prepared with combination of hybrid yarn, PP, glass combination. Further studies will investigate the effect of glass content in fabric, effect of weave, warps and filling density, number of layer plays significant role in deciding mechanical properties of thermoplastic laminates.

Keywords: thermoplastic, preform, laminates, hybrid yarn, glass

Procedia PDF Downloads 566